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TOPLINE:
Removing race and incorporating social determinants of health (SDOH) into the pooled cohort risk equations (PCEs) for predicting atherosclerotic cardiovascular disease (ASCVD) outcomes made no difference to patients’ risk scores.
METHODOLOGY:
- Primary prevention guidelines recommend using risk prediction algorithms to assess the 10-year ASCVD risk, with the currently recommended PCEs including race.
- Researchers evaluated the incremental value of revised risk prediction equations excluding race and introducing SDOH in 11,638 participants from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort.
- Participants were aged between 45 and 79 years, had no history of ASCVD, and were not taking statins.
- Participants were followed up to 10 years for incident ASCVD, including myocardial infarction, coronary heart disease death, and fatal and nonfatal stroke.
TAKEAWAY:
- Risk prediction equations performed similarly in race- and sex-stratified PCEs (C-statistic [95% CI])
- Black female: 0.71 (0.68-0.75); Black male: 0.68 (0.64-0.73); White female: 0.77 (0.74-0.80); White male: 0.68 (0.65-0.71)
- Race-free sex-specific PCEs yielded similar discrimination as race- and sex-stratified PCEs (C-statistic [95% CI]):
- Black female: 0.71 (0.67-0.75); Black male: 0.68 (0.63-0.72); White female: 0.76 (0.73-0.80); White male: 0.68 (0.65-0.71)
- The addition of SDOH to race-free sex-specific PCEs did not improve model performance (C-statistic [95% CI]):
- Black female: 0.72 (0.68-0.76); Black male: 0.68 (0.64-0.72); White female: 0.77 (0.74-0.80); White male: 0.68 (0.65-0.71)
IN PRACTICE:
“The major takeaway is we need to rethink the idea of race in cardiovascular risk prediction,” lead author Arnab Ghosh, MD, assistant professor of medicine at Weill Cornell Medical College and a hospitalist at New York-Presbyterian/Weill Cornell Medical Center, said in a press release.
“It’s essential for clinicians and scientists to consider how to appropriately address the health effects of race as a social construct, which has contributed to health disparities in cardiovascular outcomes,” Dr. Ghosh added.
SOURCE:
The study led by Dr. Ghosh was published online on December 6, 2023, in JAMA Cardiology with an Editor’s Note.
LIMITATIONS:
The study required informed consent for inclusion, which may have led to selection bias.
The REGARDS cohort’s SDOH may not have captured all social and socioeconomic influences on ASCVD outcomes.
DISCLOSURES:
The research was funded by the National Institute of Neurological Disorders and Stroke and the National Institute on Aging of the National Institutes of Health, Department of Health and Human Services, and others. Some authors declared receiving funding, grants, or personal fees from various sources.
A version of this article appeared on Medscape.com.
TOPLINE:
Removing race and incorporating social determinants of health (SDOH) into the pooled cohort risk equations (PCEs) for predicting atherosclerotic cardiovascular disease (ASCVD) outcomes made no difference to patients’ risk scores.
METHODOLOGY:
- Primary prevention guidelines recommend using risk prediction algorithms to assess the 10-year ASCVD risk, with the currently recommended PCEs including race.
- Researchers evaluated the incremental value of revised risk prediction equations excluding race and introducing SDOH in 11,638 participants from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort.
- Participants were aged between 45 and 79 years, had no history of ASCVD, and were not taking statins.
- Participants were followed up to 10 years for incident ASCVD, including myocardial infarction, coronary heart disease death, and fatal and nonfatal stroke.
TAKEAWAY:
- Risk prediction equations performed similarly in race- and sex-stratified PCEs (C-statistic [95% CI])
- Black female: 0.71 (0.68-0.75); Black male: 0.68 (0.64-0.73); White female: 0.77 (0.74-0.80); White male: 0.68 (0.65-0.71)
- Race-free sex-specific PCEs yielded similar discrimination as race- and sex-stratified PCEs (C-statistic [95% CI]):
- Black female: 0.71 (0.67-0.75); Black male: 0.68 (0.63-0.72); White female: 0.76 (0.73-0.80); White male: 0.68 (0.65-0.71)
- The addition of SDOH to race-free sex-specific PCEs did not improve model performance (C-statistic [95% CI]):
- Black female: 0.72 (0.68-0.76); Black male: 0.68 (0.64-0.72); White female: 0.77 (0.74-0.80); White male: 0.68 (0.65-0.71)
IN PRACTICE:
“The major takeaway is we need to rethink the idea of race in cardiovascular risk prediction,” lead author Arnab Ghosh, MD, assistant professor of medicine at Weill Cornell Medical College and a hospitalist at New York-Presbyterian/Weill Cornell Medical Center, said in a press release.
“It’s essential for clinicians and scientists to consider how to appropriately address the health effects of race as a social construct, which has contributed to health disparities in cardiovascular outcomes,” Dr. Ghosh added.
SOURCE:
The study led by Dr. Ghosh was published online on December 6, 2023, in JAMA Cardiology with an Editor’s Note.
LIMITATIONS:
The study required informed consent for inclusion, which may have led to selection bias.
The REGARDS cohort’s SDOH may not have captured all social and socioeconomic influences on ASCVD outcomes.
DISCLOSURES:
The research was funded by the National Institute of Neurological Disorders and Stroke and the National Institute on Aging of the National Institutes of Health, Department of Health and Human Services, and others. Some authors declared receiving funding, grants, or personal fees from various sources.
A version of this article appeared on Medscape.com.
TOPLINE:
Removing race and incorporating social determinants of health (SDOH) into the pooled cohort risk equations (PCEs) for predicting atherosclerotic cardiovascular disease (ASCVD) outcomes made no difference to patients’ risk scores.
METHODOLOGY:
- Primary prevention guidelines recommend using risk prediction algorithms to assess the 10-year ASCVD risk, with the currently recommended PCEs including race.
- Researchers evaluated the incremental value of revised risk prediction equations excluding race and introducing SDOH in 11,638 participants from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort.
- Participants were aged between 45 and 79 years, had no history of ASCVD, and were not taking statins.
- Participants were followed up to 10 years for incident ASCVD, including myocardial infarction, coronary heart disease death, and fatal and nonfatal stroke.
TAKEAWAY:
- Risk prediction equations performed similarly in race- and sex-stratified PCEs (C-statistic [95% CI])
- Black female: 0.71 (0.68-0.75); Black male: 0.68 (0.64-0.73); White female: 0.77 (0.74-0.80); White male: 0.68 (0.65-0.71)
- Race-free sex-specific PCEs yielded similar discrimination as race- and sex-stratified PCEs (C-statistic [95% CI]):
- Black female: 0.71 (0.67-0.75); Black male: 0.68 (0.63-0.72); White female: 0.76 (0.73-0.80); White male: 0.68 (0.65-0.71)
- The addition of SDOH to race-free sex-specific PCEs did not improve model performance (C-statistic [95% CI]):
- Black female: 0.72 (0.68-0.76); Black male: 0.68 (0.64-0.72); White female: 0.77 (0.74-0.80); White male: 0.68 (0.65-0.71)
IN PRACTICE:
“The major takeaway is we need to rethink the idea of race in cardiovascular risk prediction,” lead author Arnab Ghosh, MD, assistant professor of medicine at Weill Cornell Medical College and a hospitalist at New York-Presbyterian/Weill Cornell Medical Center, said in a press release.
“It’s essential for clinicians and scientists to consider how to appropriately address the health effects of race as a social construct, which has contributed to health disparities in cardiovascular outcomes,” Dr. Ghosh added.
SOURCE:
The study led by Dr. Ghosh was published online on December 6, 2023, in JAMA Cardiology with an Editor’s Note.
LIMITATIONS:
The study required informed consent for inclusion, which may have led to selection bias.
The REGARDS cohort’s SDOH may not have captured all social and socioeconomic influences on ASCVD outcomes.
DISCLOSURES:
The research was funded by the National Institute of Neurological Disorders and Stroke and the National Institute on Aging of the National Institutes of Health, Department of Health and Human Services, and others. Some authors declared receiving funding, grants, or personal fees from various sources.
A version of this article appeared on Medscape.com.